wikiRivers: Effectively communicating river level information to user groups
As a result of societal transformations, political governance shifts, and advances in ICT, online information has become a crucial dimension in efforts by public authorities to make citizens better stewards of the environment. Yet their environmental information provision often lacks knowledge of end users’ rationales, behaviours and appreciations. This project revolves around dynamic river level information provided by an environmental regulator – updated once a day or more, and collected by a sensor network of 333 gauging stations along 232 Scottish rivers. Employing an elaborate mixed methods approach with qualitative and quantitative elements, we examine if profiling of web page user groups (phase 1 of this study) and the subsequent employment of a specially designed Natural Language Generation (NLG) system (phase 2), could be steps towards more effective online information provision. In phase 1, we have been identifying profiles for the three main user groups: fishing, flood risk related, and paddling. The clear delineation and existence of well-distinguishable rationales and characteristics is in itself an argument for profiling; the same river level information is used in entirely different ways by the three groups. For phase 2 we have been constructing an advanced online experiment that implemented NLG based on live and dynamic river level data. First findings show that dynamic textual information can be of much value in translating complex, dynamic technical information into straightforward messages for the specific purposes of the user groups. This study shows that tailored NLG can be of much use in more effective online environmental information provision.